1. Field of the Invention
The present relates to a method and an apparatus for allocating network rates. In particular, it relates to a scenario like a network resource allocation optimization problem, in which the operator would like to take into account the service quality perceived by the user.
2. Description of the Related Art
Network resource management and resource allocation in wireless network has become a priority for the mobile network operator due to a continuous increasing demand of video applications. In order to use the network resource efficiently and to achieve user satisfaction, the network needs to understand the application requirements, e.g., through deep packet inspection in the network. This enables the network to know the sensitivity of the video content and the packet dependency. The video sensitivity is the relationship of the video quality perceived by the user in dependence of network parameters such as for example the data rate and the packet loss rate. For instance, a video that contains a dynamic scene (e.g. sport) requires a higher data rate, and it is more sensitive to the packet loss. The packet dependency tells the network about the importance of the packet, and therefore, allowing the network to prioritize different packets. For instance, for a video codec using a group of pictures according to an I-B-P-B-P-B- . . . order, transmitting a packet containing an I-frame has a higher priority than packets of P-frame or B-frame, since the P-frame and B-frame could not be correctly decoded if the I-frame, on which it is dependent, is not being sent to the receiver successfully.
Allocating the network resources to multiple video streams containing different video contents is a challenging task for the network operator, since the network operator has to know how much network resources should be given to which video streams in order to efficiently use its limited network resource while keeping all users being served in the network satisfied.
Optimizing the network resource allocation with a consideration of different layers' abstracted information (e.g. application model/application sensitivity, channel quality condition) has been first introduced for elastic applications (e.g. file transfer application) (see e.g. F. P. Kelly, “Charging and rate control for elastic traffic,” European Transaction of Telecommunication, vol. 8, pp. 33-37, January 1997). Later, in “S. Khan, S. Duhovnikov, E. Steinbach, and W. Kellerer, “MOS-based multiuser multiapplication cross-layer optimization for mobile multimedia communication,” Advances in Multimedia, 2007, article ID 94918”, the resource allocation is optimized across different applications by using the Mean Opinion Score (MOS), which is a quality measure which was originally proposed for voice application, as a common metric for user perceived quality measure (see e.g. ITU-T Recommendation P.800, “Method for subjective determination of transmission quality,” August 1996). The optimal resource allocation is dependent on the objective function set by the network operator. There are several ways of setting an objective function for the network resource optimization problem such as a maximum of the average quality of all users (called MaxSum), or having a similar quality for all users regardless of application type and channel quality condition (called MaxMin). In addition, the network operator may also set a minimum guarantee quality for all users, and then adapts the resource allocation so as to achieve the same quality that is equal or higher than the guarantee quality (MaxMin−MinMOS), or so as to achieve maximum average quality (MaxSum−MinMOS).
Prior art addressing the problem of how the network resources are allocated to the user only are related to cross-layer optimization, in which the network resources allocation is optimized based on the information abstracted from different layers. In S. Khan, S. Duhovnikov, E. Steinbach, and W. Kellerer, “MOS-based multiuser multiapplication cross-layer optimization for mobile multimedia communication,” Advances in Multimedia, 2007, article ID 94918, or in L.-U. Choi, M. T. Ivrlac, E. Steinbach, and J. A. Nossek, “Bottom-up approach to cross-layer design for video transmission over wireless channels,” in Proc. IEEE Vehicular Technology Conference 2005-Spring (VTC'S05), vol. 5, Stockholm, Sweden, May 30-Jun. 1, 2005, pp. 3019-3025, or in U.S. Pat. No. 7,609,652B2—Apparatus and Method for Controlling an Operation of a Plurality of Communication Layers, they take the information from application, network, MAC and physical layer into account. Based on the objective function set for the optimization problem, the network resources are allocated differently. For example, a network may want to achieve a maximum of the average user perceived quality of all users like in Khan et al. Another approach could be to allocate the network resources such that all users perceive a similar quality of service, like in B. Radunovic and J.-Y. Le Boudec, “A unified framework for max-min and min-max fairness with applications,” IEEE/ACM Trans. on Networking, vol. 15, no. 5, pp. 1073-1083, October 2007, or in U.S. Pat. No. 5,675,576-Congestion control system and method for packet switched networks providing max-min fairness. However, despite there are many different approaches to optimize resource allocation, none of the known approaches can deal efficiently with the problem how to avoid noticeable quality fluctuations.
It is therefore desirable to provide an approach which can effectively deal with this problem.